Singular perturbation composite learning control method of elastic aircraft based on interference observation

Abstract

The invention relates to a singular perturbation composite learning control method of an elastic aircraft based on interference observation. According to the method, a longitudinal channel model of the elastic aircraft is decomposed into a speed subsystem and a posture subsystem at first; and PID control is adopted for the speed subsystem, the posture subsystem is analyzed by using the singular perturbation theory, and rigid-flexible mode decoupling and fast and slow time scale separation are realized. A sliding mode control method is designed to control an elastic fast-changing subsystem; anda back stepping method is designed to control a posture slow change subsystem, meanwhile unknown dynamics is approached by using a composite neural network, and a nonlinear observer is designed to compensate the external disturbances. Based on the controller designed above, precise tracking of height and speed is achieved.

Description

technical field [0001] The invention relates to an aircraft control method, in particular to a singular perturbation compound learning control method for an elastic aircraft based on disturbance observation, and belongs to the field of aircraft control. Background technique [0002] Due to the use of lightweight materials, the aircraft has structural elasticity problems, which will not only lead to a decrease in the control accuracy of the system, but may also cause the fuselage to break. At the same time, due to the complexity of the flight environment and system structure, the aircraft dynamics model has unknown nonlinearity, the intelligent control technology based on the neural network has received widespread attention, but most of the existing intelligent approximation methods are only based on the Lyapunov stability design weight update law , the lack of mining of internal information violates the original intention of effectively estimating unknown dynamics. "Robust ...

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Problems solved by technology

[0002] Due to the use of lightweight materials, the aircraft has structural elasticity problems, which will not only lead to a decrease in the control accuracy of the system, but may also cause the fuselage to break

At the same time, due to the complexity of the flight environment and system structure, the aircraft dynamics model has unknown nonlinearity, the intelligent control technology based on the neural network has received widespread attention, but most of the existing intelligent approximation methods are only based on the Lyapunov stability design weight update law , the lack of mining of internal information violates the original intention of effectively estimating unknown dynamics

"Robust adaptive neural control of flexible hypersonicflight vehicle with dead-zone input nonlinearity" (Bin Xu, "NonlinearDynamics", 2015, 80:1509-1520) regards the elastic mode as a disturbance item, and uses the robust item to control the elastic mode Compensation solves the problem of elastic body control of hypersonic vehicles, but this method does not conduct in-depth analysis and processing of elastic modes, and does not consider the influence of external disturbances on the system, so the control accuracy of the system cannot be guaranteed

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